AI Engineer (Junior)

About Gyansys:

GyanSys is a global mid-tier systems integrator with over 20 years of experience, headquartered in the US. With 3,000+ employees across 12 countries, we serve 160+ enterprise customers across Manufacturing, Industrial, Consumer, Life Sciences, and High-Tech industries.

We specialize in Digital Transformation through SAP, Salesforce, Databricks, Snowflake, Application Modernization, and AI-driven solutions.

We are seeking a AI Engineer to build and deliver production-grade agentic AI systems for enterprise use. The engineer will develop multi-agent workflows, integrate large language models into existing enterprise systems, and support the deployment and automation needed to run them reliably and securely in production.

This is a hands-on engineering engagement. The work centers on building agents, orchestration logic, and supporting infrastructure that performs under real production workloads, not on proof-of-concept or advisory work.

Scope of Work

• Build AI agents and multi-agent systems using frameworks with LangGraph and LangChain tools.

• Develop and tune prompt engineering workflows across multiple LLMs (GPT, Claude, LLaMA), balancing reliability, cost, and latency.

• Develop REST APIs, WebSocket services, and event-driven pipelines for real-time AI services that remain stable under load.

• Automate testing and releases through Jenkins CI/CD, and maintain code and documentation standards using Git, Jira, and Confluence.

• Deployment of AI Application in enterprise adhering to best practices

• Use AI-augmented development tools such as Claude Code and Codex to accelerate delivery.

• Coordinate with platform, security, and product teams to deliver scalable, secure deployments.

Must-Have Skills

• 3-5 years in Machine Learning, AI, or a related field, with production systems delivered.

• At least 1 year building custom Agentic AI applications

• Strong Python skills and sound modern development practices.

• Hands-on experience with LLMs and prompt engineering across the full application lifecycle.

• Demonstrated experience building AI agents with LangGraph.

• Familiarity with at least one enterprise cloud AI platform for building and deploying agentic applications, such as Azure AI Foundry, AWS Bedrock, or Google Gemini Enterprise, including cloud-native deployment practices.

• Working knowledge of REST APIs, WebSockets, and event-driven systems.

• Proficiency with CI/CD tooling (Jenkins) and version control (Git).

• Fluency with AI-augmented development tools for rapid prototyping.

• Strong written and verbal communication, an analytical approach to problem-solving, and the ability to work independently within a cross-functional team.

• Data layer curations and integration with source system for agentic application

Good-to-Have Skills

• Familiarity with Databricks.

• Exposure to MLOps/LLMOps workflows and application monitoring.

• Knowledge of enterprise security, compliance, and governance for AI systems.

• Familiarity with code and model lifecycle management practices.